Explore publications.

The purpose of the study was to investigate the importance of Teacher Professional Development in the implementation of online teaching as a tool for distance learning since the onset of COVID- 19. Before the outburst of the coronavirus pandemic, lecturers were used to face-to-face contact sessions, and most of the students did not have laptops. So, the distressing experience of COVID-19 has catalyzed the need for continuing professional teacher development. The study employed the theory of reasoned behavior and the theory of planned behaviour. The theory of reasoned action aims to explain the relationship between attitudes and behaviours within human action. It is used to predict how individuals will behave based on their pre-existing attitudes and behavioural intentions. The latter includes behavioural control as an additional determinant of intentions and behaviour. The study adopted qualitative methodology and employed the case study. The data was collected through interviews with four university lecturers, who were chosen through purposive sampling technique. The data revealed that most teachers perceived online teaching as a good intervention during the period of COVID- 19. However, teachers lacked training and experience when it comes to online teaching. This resulted in lot of uncertainty when it came to online teaching, and frustration for older teachers. In conclusion, the paper highlighted the need for teacher development in the form of in-service training and suggested that teachers should register for short courses on online learning, implementing mentorship programs by the tertiary institutions.

This study was inspired by the observation that code-switching is often discouraged in foreign language schools, where the target language and native language are strictly separated, with the target language designated as the 'official' language of instruction. The study sought to examine instances of code-switching in English as a First Additional Language (EFAL) acquisition among Sesotho native speakers in the Intermediate Phase in South Africa. Furthermore, it sought to illustrate the application of tag-code-switching, inter-sentential code-switching, and intra-sentential code-switching in English First Additional Language (EFAL) education for Sesotho native speakers in the Intermediate Phase in South Africa. This paper studied a particular multilingual phenomena, code-switching. While other linguistic behaviours exist, code-switching is the most popular in additional language contexts in South Africa. This research was founded on a literature review of code-switching in additional language situations. The paper examined the three roles of code-switching: repetition, emotional, and floor-holding. It also provided instances of how tag-code-switching, inter-sentential code-switching, and intra-sentential code-switching might be utilised by Sesotho home language learners to improve their comprehension of EFAL. One finding of the study is that, similar to translanguaging, code-switching fosters a sense of belonging and ownership among learners, and it is generally more accessible for the EFAL student to acquire knowledge from familiar concepts to unfamiliar ones. Another conclusion is that learners' restricted engagement in academic activities, attributable to their inadequate language proficiency, also impacts their motivation. The study advocates for the implementation of code-switching to improve learners' classroom involvement by allowing them to utilise their native language in the acquisition of a second language. The impact of code-switching on Sesotho home language learners' comprehension of EFAL in the Intermediate Phase in South Africa remains undetermined, necessitating further investigation into this important issue.

This paper aims to examine the impact of export diversification on business formation in Africa. The study used a panel dataset comprising 10 African countries (Algeria, Gabon, Lesotho, Morocco, Nigeria, Sierra Leone, Togo, Tunisia, Uganda and Zambia) observed annually from 2008 to 2018. The model was estimated using an instrumental variable regression approach within a count data framework and the difference-in-difference method. Main findings of the study demonstrate that (i) export diversification facilitates the formation of new businesses in the sampled countries, (ii) the odds of a business start-up increase by 1.7 – 3.5 times in response to a percentage point increase in export diversification, and finally (iii) business start-ups are at least 95 percent higher in countries with high export diversification compared to countries with narrow export baskets. These findings emphasize the need for policies aimed at moving away from concentrated export baskets towards more diversified ones to leverage entrepreneurial effort in the selected African countries.

Technological development has witnessed tremendous and an increase in business interactions as they execute their daily business. Information technology and broadband are significant drivers of productivity and efficiency growth for small firms as they expand their market. This development has raised growing concerns as it relates to data and information security, infrastructure, and related resources  due to an increase in cybersecurity hazards faced  by Small to Medium Enterprises globally. In South Africa, although, during the first four months of 2022, cyber-attacks decreased by 13% to account for 419506 internet attacks, this statistic remains high enough for concern. To counter escalating cybersecurity risks, organizations must have a cybersecurity strategy to safeguard their operations, clients, data, and infrastructure. The threat landscape is changing over time, and despite ongoing attempts to strengthen security, they don't appear to be enough to prevent evolving cyberattacks. The study aims to identify cybersecurity threats facing Small to Medium Enterprises in South Africa by reviewing the literature and identifying key Cybersecurity challenges. It also examines the strategies, resources, and techniques used in South Africa to reduce cybersecurity threats. Lastly, the paper recommends adopting a comprehensive Cybersecurity strategy to build future-proof cybersecurity for Small to Medium Enterprises in South Africa.

This scoping review aims to explore various Deep Learning and Symbolic Artificial Intelligence (AI) models that can be integrated into explainable hybrid AI for the purpose of detecting COVID-19 based on Computerized Tomography (CT) scans. We followed the PRISMA-ScR framework as the foundation for our scoping review protocol. Our approach included a thorough search across 13 databases, complemented by an additional random internet search for relevant articles. Due to the voluminous number of articles returned, the search was further narrowed using the keywords: Deep Learning, Symbolic AI and Hybrid AI. These keywords were used because they are more visible in the earmarked literature. A screening of all articles by title was performed to remove duplicates. The final screening process centered on the publication year, ensuring that all considered articles fell within the range of 2019 to 2023, inclusive. Subsequently, abstract or text synthesis was conducted. Our search query retrieved a total of 3,312 potential articles from the thirteen databases, and an additional 12 articles from a random internet search, resulting in a cumulative count of 3,324 identified articles. After the deduplication and screening steps, 260 articles met our inclusion criteria. These articles were categorized based on the year of publication, the type of aim, and the type of AI used. An analysis of the year of publication revealed a linear trend, indicating growth in the field of Hybrid AI. Out of the five aim categories identified, we deliberately excluded articles that lacked a specified aim. It's noteworthy that 3% of the articles focused on the integration of AI models. The low percentage value suggests that the integration aspect is overlooked, thereby transcripting the integration of Deep Learning and symbolic AI into hybrid AI as an area worth exploring. This scoping review gives an overview of how a Deep Learning and Symbolic AI-based framework has been used in the detection of COVID-19 based on CT scans.